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Research ArticleOpen accessPhrase in the titleHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,016 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleA Proposed an Enhanced Authentication and Dual Encryption Algorithm: Secured Video Transmission in Surgical Tele-TrainingAnil Wagle, Abeer Alsadoon, P.W.C. Prasad et al.Implementation of tele-training for trainee surgeons has been slow to date as current standards of video transmission do not meet requirements for security, speed and clarity for such videos. The aim of this paper is to increase security by providing enhanced authentication as well as improving the overall throughput of the system. The proposed solution consists of a dual encryption … …American Journal of Applied Sciences, Vol. 15, Issue 10 · 28 Dec 2018 · 7,772 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSome Statistical Solutions and Methods in Evaluation of Efficiency in Sport and Effectiveness in the Phenomenon of Sportsmen' TrainingGheorghe Săvoiu, Ion Iorga, Marian Creţu, Ion MihăilăProblem statement: A general method for evaluation of efficiency in sport and effectiveness in the phenomenon of sportsmen’s training was proposed. Approach: The method of four “E” was a frame method focused on communication and evaluation, where efficiency acquired an essential importance and its variation related to the initial programme, with its time or space details, respectively related to the … …Journal of Social Sciences, Vol. 7, Issue 3 · 18 Jul 2011 · 7,878 accessesView PDFCite
Research ArticleOpen accessIn the keywordsStochastic Estimator-Based Wireless Traffic Control SchemesFrancis Joseph Ogwu, Mohammad Talib, Ganiyu Adesola AderounmuRecent works on Available Bit Rate (ABR) traffic control have generated efficient control schemes for ABR traffic on Asynchronous Transfer Mode (ATM) network. This study examines the improved performance envisaged if these control schemes adjust dynamically to the varying ABR bandwidth capacity in a stochastic manner instead of conventional deterministic approach .The performance difference between setting explicit rate deterministically for … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 7,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Social Media Face Emotion Recognition Using a Fuzzy ELM ApproachShuchi Gupta, K. Viswanath, S. Gokul Pran et al.Our computational tools for searching, exploring, and sharing personal photographs are falling behind the rapid pace at which these images are being captured digitally. The use of automatic face recognition to categorize images according to the people in them is one potential solution. Accurate recognition on the Internet scale, however, presents the seemingly insurmountable challenge of picking out specific people … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,978 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach Based on Federated Learning for the Identification of Man in the Middle Attacks in IOT Networks Using BlockchainSarumathi S, Juliet Johny, Minal Khandare et al.Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning’s … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,613 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite